Abstract : Droplet microfluidics - i.e. the use of droplets as microreactors - offers significant advantages for the study of biological systems. In this work, we present a new platform for the production and manipulation of microfluidic droplets in view of measuring the evolution of biochemical reactions. Contrary to existing approaches, our device uses gradients of confinement to produce a single drop on demand and guide it to a pre-determined location. In this way, two nanoliter drops containing different reagents can be placed in contact and merged together in order to trigger a chemical reaction. Then, an analysis of the observed reaction front yields the reaction rate. We start with the case of one step reactions. We derive a one dimensional reaction-diffusion model for the reaction front and compare numerical and analytical solutions of our model to experiments held in our microsystem. Then, we turn our attention to the case of enzymatic reactions. First, we show how the device operation can be parallelized in order to react an initial sample with a range of compounds or concentrations and we perform standard well-mixed enzyme assays with our parallelized chip, thereby mimicking titer plate assays in droplets. Second, we build onto our reaction-diffusion model to predict the rate of fast enzymatic reactions held in our device. Again, numerical and analytical solutions of our model are compared to experiments done in droplets which yields measurements of the kinetic parameters of the reaction at play.